{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2011:77FJVZW7DKW466RGEAMJ7FQ7YR","short_pith_number":"pith:77FJVZW7","canonical_record":{"source":{"id":"1101.0391","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2011-01-02T09:10:20Z","cross_cats_sorted":[],"title_canon_sha256":"0c8d5b09bd18e6871f14e836625843fced60bf90cbe1783408353b93872995ce","abstract_canon_sha256":"ca32ba17adea2ad4ed88168705e8679ca12c0f1fd739f5c1e5eefbef778dd75f"},"schema_version":"1.0"},"canonical_sha256":"ffca9ae6df1aadcf7a2620189f961fc46866726fb00a1d971be7cd8b61941729","source":{"kind":"arxiv","id":"1101.0391","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1101.0391","created_at":"2026-05-18T04:32:02Z"},{"alias_kind":"arxiv_version","alias_value":"1101.0391v2","created_at":"2026-05-18T04:32:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1101.0391","created_at":"2026-05-18T04:32:02Z"},{"alias_kind":"pith_short_12","alias_value":"77FJVZW7DKW4","created_at":"2026-05-18T12:26:22Z"},{"alias_kind":"pith_short_16","alias_value":"77FJVZW7DKW466RG","created_at":"2026-05-18T12:26:22Z"},{"alias_kind":"pith_short_8","alias_value":"77FJVZW7","created_at":"2026-05-18T12:26:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2011:77FJVZW7DKW466RGEAMJ7FQ7YR","target":"record","payload":{"canonical_record":{"source":{"id":"1101.0391","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2011-01-02T09:10:20Z","cross_cats_sorted":[],"title_canon_sha256":"0c8d5b09bd18e6871f14e836625843fced60bf90cbe1783408353b93872995ce","abstract_canon_sha256":"ca32ba17adea2ad4ed88168705e8679ca12c0f1fd739f5c1e5eefbef778dd75f"},"schema_version":"1.0"},"canonical_sha256":"ffca9ae6df1aadcf7a2620189f961fc46866726fb00a1d971be7cd8b61941729","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:32:02.401833Z","signature_b64":"Iklty2D8wHqM2L1Z78YlJ02N7NFnCxZFRr6xuA9do6mldhu+AsCOLgp394o2SJ+UXm/Q06a0kjpLoubHBkeHAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ffca9ae6df1aadcf7a2620189f961fc46866726fb00a1d971be7cd8b61941729","last_reissued_at":"2026-05-18T04:32:02.401432Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:32:02.401432Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1101.0391","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T04:32:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2151ibV/yt8pEh4hMsix4uycoxRjLCICbZpsAMK2nJzVv3bEQEJpaM1snDqwqZT7CgymcwIdvKwFXJXCpWjdDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T17:40:35.329658Z"},"content_sha256":"2a24d31cb4fd0c932b58c13ec97e14296104158183386f7f6a9b2809d57eddc3","schema_version":"1.0","event_id":"sha256:2a24d31cb4fd0c932b58c13ec97e14296104158183386f7f6a9b2809d57eddc3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2011:77FJVZW7DKW466RGEAMJ7FQ7YR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bayesian inference for a class of latent Markov models for categorical longitudinal data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Francesco Bartolucci, Silvia Pandolfi","submitted_at":"2011-01-02T09:10:20Z","abstract_excerpt":"We propose a Bayesian inference approach for a class of latent Markov models. These models are widely used for the analysis of longitudinal categorical data, when the interest is in studying the evolution of an individual unobservable characteristic. We consider, in particular, the basic latent Markov, which does not account for individual covariates, and its version that includes such covariates in the measurement model. The proposed inferential approach is based on a system of priors formulated on a transformation of the initial and transition probabilities of the latent Markov chain. This s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1101.0391","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T04:32:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yRVOGtR+r6BqvKcltm7FroUCabVlSmoUPhIbZlZCC3CiFmqie3r829/Spw2OxiBmc2XaCCqdfBOtcHBXZKAwBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T17:40:35.330008Z"},"content_sha256":"d77c57120ff3e731db286c414b88acfd995290bc56e4a3e5b095f78a5b4f45d1","schema_version":"1.0","event_id":"sha256:d77c57120ff3e731db286c414b88acfd995290bc56e4a3e5b095f78a5b4f45d1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/77FJVZW7DKW466RGEAMJ7FQ7YR/bundle.json","state_url":"https://pith.science/pith/77FJVZW7DKW466RGEAMJ7FQ7YR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/77FJVZW7DKW466RGEAMJ7FQ7YR/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-05T17:40:35Z","links":{"resolver":"https://pith.science/pith/77FJVZW7DKW466RGEAMJ7FQ7YR","bundle":"https://pith.science/pith/77FJVZW7DKW466RGEAMJ7FQ7YR/bundle.json","state":"https://pith.science/pith/77FJVZW7DKW466RGEAMJ7FQ7YR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/77FJVZW7DKW466RGEAMJ7FQ7YR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2011:77FJVZW7DKW466RGEAMJ7FQ7YR","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"ca32ba17adea2ad4ed88168705e8679ca12c0f1fd739f5c1e5eefbef778dd75f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2011-01-02T09:10:20Z","title_canon_sha256":"0c8d5b09bd18e6871f14e836625843fced60bf90cbe1783408353b93872995ce"},"schema_version":"1.0","source":{"id":"1101.0391","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1101.0391","created_at":"2026-05-18T04:32:02Z"},{"alias_kind":"arxiv_version","alias_value":"1101.0391v2","created_at":"2026-05-18T04:32:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1101.0391","created_at":"2026-05-18T04:32:02Z"},{"alias_kind":"pith_short_12","alias_value":"77FJVZW7DKW4","created_at":"2026-05-18T12:26:22Z"},{"alias_kind":"pith_short_16","alias_value":"77FJVZW7DKW466RG","created_at":"2026-05-18T12:26:22Z"},{"alias_kind":"pith_short_8","alias_value":"77FJVZW7","created_at":"2026-05-18T12:26:22Z"}],"graph_snapshots":[{"event_id":"sha256:d77c57120ff3e731db286c414b88acfd995290bc56e4a3e5b095f78a5b4f45d1","target":"graph","created_at":"2026-05-18T04:32:02Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"We propose a Bayesian inference approach for a class of latent Markov models. These models are widely used for the analysis of longitudinal categorical data, when the interest is in studying the evolution of an individual unobservable characteristic. We consider, in particular, the basic latent Markov, which does not account for individual covariates, and its version that includes such covariates in the measurement model. The proposed inferential approach is based on a system of priors formulated on a transformation of the initial and transition probabilities of the latent Markov chain. This s","authors_text":"Francesco Bartolucci, Silvia Pandolfi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2011-01-02T09:10:20Z","title":"Bayesian inference for a class of latent Markov models for categorical longitudinal data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1101.0391","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:2a24d31cb4fd0c932b58c13ec97e14296104158183386f7f6a9b2809d57eddc3","target":"record","created_at":"2026-05-18T04:32:02Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"ca32ba17adea2ad4ed88168705e8679ca12c0f1fd739f5c1e5eefbef778dd75f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2011-01-02T09:10:20Z","title_canon_sha256":"0c8d5b09bd18e6871f14e836625843fced60bf90cbe1783408353b93872995ce"},"schema_version":"1.0","source":{"id":"1101.0391","kind":"arxiv","version":2}},"canonical_sha256":"ffca9ae6df1aadcf7a2620189f961fc46866726fb00a1d971be7cd8b61941729","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ffca9ae6df1aadcf7a2620189f961fc46866726fb00a1d971be7cd8b61941729","first_computed_at":"2026-05-18T04:32:02.401432Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T04:32:02.401432Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Iklty2D8wHqM2L1Z78YlJ02N7NFnCxZFRr6xuA9do6mldhu+AsCOLgp394o2SJ+UXm/Q06a0kjpLoubHBkeHAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T04:32:02.401833Z","signed_message":"canonical_sha256_bytes"},"source_id":"1101.0391","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2a24d31cb4fd0c932b58c13ec97e14296104158183386f7f6a9b2809d57eddc3","sha256:d77c57120ff3e731db286c414b88acfd995290bc56e4a3e5b095f78a5b4f45d1"],"state_sha256":"3b6fcbac5f9e8050e3b3cf123674385cb208048f0eefb65623f40bd040ca9992"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sfqpHSNHNrMn0usAFSOwFwIYUEOglO9STGoSSOpk0zEQLHMa+4zykZScDMJIJ7DaOOy9XUDm3NxAuQc/5ft1Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-05T17:40:35.332004Z","bundle_sha256":"28defc925df04c595985c6301a16f4a8c9a4d9c15dd4ae872ccaba7ea84836b5"}}